Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints

TLDR

Vehicle routing and scheduling with time windows is intrinsically hard, so approximation methods are most promising for practical instances. The study designs and analyzes algorithms for vehicle routing and scheduling with time window constraints. The authors evaluate a suite of heuristics across diverse routing and scheduling scenarios varying in data type, time‑window density, tightness, positioning, and horizon length. Several heuristics excelled in different settings, with an insertion‑type heuristic consistently delivering the best performance.

Abstract

This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints. Given the intrinsic difficulty of this problem class, approximation methods seem to offer the most promise for practical size problems. After describing a variety of heuristics, we conduct an extensive computational study of their performance. The problem set includes routing and scheduling environments that differ in terms of the type of data used to generate the problems, the percentage of customers with time windows, their tightness and positioning, and the scheduling horizon. We found that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.